Package: Rosenbrock 0.1.0

Martin Wiegand

Rosenbrock: Extended Rosenbrock-Type Densities for Markov Chain Monte Carlo (MCMC) Sampler Benchmarking

New Markov chain Monte Carlo (MCMC) samplers new to be thoroughly tested and their performance accurately assessed. This requires densities that offer challenging properties to the novel sampling algorithms. One such popular problem is the Rosenbrock function. However, while its shape lends itself well to a benchmark problem, no codified multivariate expansion of the density exists. We have developed an extension to this class of distributions and supplied densities and direct sampler functions to assess the performance of novel MCMC algorithms. The functions are introduced in "An n-dimensional Rosenbrock Distribution for MCMC Testing" by Pagani, Wiegand and Nadarajah (2019) <arxiv:1903.09556>.

Authors:Martin Wiegand

Rosenbrock_0.1.0.tar.gz
Rosenbrock_0.1.0.zip(r-4.7)Rosenbrock_0.1.0.zip(r-4.6)Rosenbrock_0.1.0.zip(r-4.5)
Rosenbrock_0.1.0.tgz(r-4.6-any)Rosenbrock_0.1.0.tgz(r-4.5-any)
Rosenbrock_0.1.0.tar.gz(r-4.7-any)Rosenbrock_0.1.0.tar.gz(r-4.6-any)
Rosenbrock_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
Rosenbrock/json (API)

# Install 'Rosenbrock' in R:
install.packages('Rosenbrock', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues

On CRAN:

Conda:

archivedpackagesr-universe

1.70 score 5 stars 1 scripts 173 downloads 5 exports 1 dependencies

Last updated from:0e9ae6590f (on package/Rosenbrock). Checks:9 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK101
source / vignettesOK136
linux-release-x86_64OK96
macos-release-arm64OK68
macos-oldrel-arm64OK87
windows-develOK63
windows-releaseOK59
windows-oldrelOK63
wasm-releaseOK90

Exports:devendfulldhybridrevenrhybrid

Dependencies:MASS